An InfoPackage is used to specify how and when to load data to BI system from different data sources. An InfoPackage contains all the information how data is loaded from source system to a data source or PSA. InfoPackage consists of condition for requesting data from a source system.

Note that using an InfoPackage in BW 3.5, you can load data in Persistence Staging Area and also in targets from source system but If you are using SAP BI 7.0 data load should be restricted to PSA only for latest versions.

In Extended Star schema, Fact tables are connected to Dimension tables and dimension table is connected to SID table and SID table is connected to master data tables. In Extended star schema you have Fact and Dimension tables are inside the cube however SID tables are outside cube. When you load the transactional data into Info cube, Dim Id’s are generated based on SID’s and these Dim id’s are used in fact tables.

In Extended Star schema one fact table can connect to 16 dimensions tables and each dimension table is assigned with 248 maximum SID tables. SID tables are also called Characteristics and each characteristic can have master data tables like ATTR, Text, etc.

In Star Schema, Each Dimension is joined to one single Fact table. Each Dimension is represented by only one dimension and is not further normalized.

Dimension Table contains set of attributes that are used to analyze the data.

Info Area in SAP BI are used to group similar types of object together. Info Area are used to manage Info Cubes and Info Objects. Each Info Objects resides in an Info Area and you can define it a folder which is used to hold similar files together.

To access data in BI source system directly. You can directly access to source system data in BI without extraction using Virtual Providers. Virtual providers can be defined as InfoProviders where transactional data is not stored in the object. Virtual providers allow only read access on BI data.

Transformation process is used to perform data consolidation, cleansing and data integration. When data is loaded from one BI object to other BI object, transformation is applied on the data. Transformation is used to convert a field of source into the target object format.

Transformation rules − Transformation rules are used to map source fields and target fields. Different rule types can be used for transformation.

A DSO is known as storage place to keep cleansed and consolidated transaction or master data at lowest granularity level and this data can be analyzed using BEx query.

A DataStore object contains key figures and charactertics fields and data from DSO can be updated using Delta update or other DataStore objects or master data. DataStore objects are commonly stored in two-dimensional transparent database tables.

Activation Queue: This is used to store the data before it is activated. The key contains request id, package id and record number. Once activation is done, request is deleted from the activation queue.

Active Data Table: This table is used to store current active data and this table contains the semantic key defined for data modeling.

Change Log: When you activate the object, changes to active data re stored in change log. Change log is a PSA table and is maintained in Administration Workbench under PSA tree.

Write optimized DSO provides a temporary storage area for large sets of data if you are executing complex transformations for this data before it is written to the DataStore object. The data can then be updated to further InfoProviders. You only have to create the complex transformations once for all data.

Write-optimized DataStore objects are used as the EDW layer for saving data. Business rules are only applied when the data is updated to additional InfoProviders.

Temporal Joins: are used to map a period of time. At the time of reporting, other InfoProviders handle time-dependent master data in such a way that the record that is valid for a pre-defined unique key date is used each time. You can define Temporal join that contains atleast one time-dependent characteristic or a pseudo time-dependent InfoProvider.

InfoCube is defined as multidimensional dataset which is used for analysis in a BEx query. An InfoCube consists of set of relational tables which are logically joined to implement star schema. A Fact table in star schema is joined with multiple dimension tables.

You can add data from one or more InfoSource or InfoProviders to an InfoCube. They are available as InfoProviders for analysis and reporting purposes.

Start Routines: The start routine is run for each Data Package after the data has been written to the PSA and before the transfer rules have been executed. It allows complex computations for a key figure or a characteristic. It has no return value. Its purpose is to execute preliminary calculations and to store them in global Data Structures. This structure or table can be accessed in the other routines. The entire Data Package in the transfer structure format is used as a parameter for the routine.

Update Routines:They are defined at the InfoObject level. It is like the Start Routine. It is independent of the DataSource. We can use this to define Global Data and Global Checks.

It is the method of dividing a table for report optimization. SAP uses fact file partitioning to improve performance. We can partition only at 0CALMONTH or 0FISCPER. Table partitioning helps to run the report faster as data is stored in the relevant partitions. Also, table maintenance becomes easier.

Universal data UD connect allows you to access Relational and multidimensional data sources and transfer the data in form of flat data. Multidimensional data is converted to flat format when Universal Data Connect is used for data transfer.

UD uses J2EE connector to allow reporting on SAP and non-SAP data. Different BI Java connectors are available for various drivers, protocols as resource adapters −